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Assessment of across-muscle coherence using multi-unit vs. single-unit recordings.

机译:使用多单元和单单元记录评估跨肌肉的连贯性。

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摘要

Coherence between electromyographic (EMG) signals has been used to identify correlated neural inputs to motor units (MUs) innervating different muscles. Simulations using a motor-unit model (Fuglevand et al. 1992) were performed to determine the ability of coherence between two multi-unit EMGs (mEMG) to detect correlated MU activity and the range of correlation strengths in which mEMG coherence can be usefully employed. Coherence between motor-unit and mEMG activities in two muscles was determined as we varied the strength of a 30-Hz periodic common input, the number of correlated MU pairs and variability of MU discharge relative to the common input. Pooled and mEMG coherence amplitudes positively and negatively accelerated, respectively, toward the strongest and most widespread correlating inputs. Furthermore, the relation between pooled and mEMG coherence was also nonlinear and was essentially the same whether correlation strength varied by changing common input strength or its distribution. However, the most important finding is that while the mEMG coherence saturates at the strongest common input strengths, this occurs at common input strengths greater than found in most physiological studies. Thus, we conclude that mEMG coherence would be a useful measure in many experimental conditions and our simulation results suggest further guidelines for using and interpreting coherence between mEMG signals.
机译:肌电图(EMG)信号之间的相干已用于识别神经支配到神经支配不同肌肉的运动单元(MU)。进行了使用运动单位模型的模拟(Fuglevand等人,1992),以确定两个多单元EMG(mEMG)之间的相干能力以检测相关的MU活动以及相关强度的范围,在其中可以有效地使用mEMG相干。当我们改变30 Hz周期性公共输入的强度,相关MU对的数量以及MU放电相对于公共输入的可变性时,确定了两条肌肉的运动单位和mEMG活动之间的连贯性。合并和mEMG相干振幅分别朝最强和最广泛的相关输入正向和负向加速。此外,合并强度和mEMG相干性之间的关系也是非线性的,并且无论相关强度是通过改变公共输入强度还是通过其分布而变化的,该关系基本相同。然而,最重要的发现是,尽管mEMG相干性在最强的通用输入强度下达到饱和,但这种情况发生在比大多数生理学研究中发现的更大的通用输入强度下。因此,我们得出结论,在许多实验条件下,mEMG相干性将是一种有用的度量,我们的仿真结果为使用和解释mEMG信号之间的相干性提供了进一步的指导。

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